from Genetic Engineering News by Richard A. Stein
The contribution of individual cells to aggregate phenotypes is of increasing interest in biology, as is evident in the rise of technologies that can resolve cell-level details from the blur of population-level generalities. Among these technologies is RNA sequencing (RNA-seq), which can take snapshots of the transcriptome, capturing fleeting expression profiles, zooming in on single cells, and exposing cell-cell variations.
At present, RNA-seq is helping researchers take a fresh look at biological phenomena such as development, malignant transformation, and the behavior of microbial populations. Already, the new views are yielding conceptual advances.
“Over the years, we have become increasingly aware that what we once treated as homogeneous populations of cells are, in fact, heterogeneous,” says Alex K. Shalek, Ph.D., a core member of the Institute for Medical Engineering and Science at MIT. “In parallel, we developed a greater appreciation for the different cellular players that are involved in shaping systems-level phenotypes.”
One of the fundamental problems in dissecting the link between genotype and phenotype is that biological samples are usually complex mixtures of cells. In certain cases, such as with blood, there is a relatively good agreement as to the identity of the major cellular components. “In other cases, such as with tumors, there are unknown mixtures of different cell types and states that drive the ensemble behaviors we observe,” adds Dr. Shalek.
One of the promises of single-cell genomics is the possibility of performing transcriptome-wide analyses of the genes expressed by each cell. By uncovering patterns in gene expression and co-variation, researchers can identify what cell types are present and which pathways are active or silent.
(read more at Genetic Engineering News…)
from Genetic Engineering News by Richard A. Stein
The contribution of individual cells to aggregate phenotypes is of increasing interest in biology, as is evident in the rise of technologies that can resolve cell-level details from the blur of population-level generalities. Among these technologies is RNA sequencing (RNA-seq), which can take snapshots of the transcriptome, capturing fleeting expression profiles, zooming in on single cells, and exposing cell-cell variations.
At present, RNA-seq is helping researchers take a fresh look at biological phenomena such as development, malignant transformation, and the behavior of microbial populations. Already, the new views are yielding conceptual advances.
One of the fundamental problems in dissecting the link between genotype and phenotype is that biological samples are usually complex mixtures of cells. In certain cases, such as with blood, there is a relatively good agreement as to the identity of the major cellular components. “In other cases, such as with tumors, there are unknown mixtures of different cell types and states that drive the ensemble behaviors we observe,” adds Dr. Shalek.
One of the promises of single-cell genomics is the possibility of performing transcriptome-wide analyses of the genes expressed by each cell. By uncovering patterns in gene expression and co-variation, researchers can identify what cell types are present and which pathways are active or silent.
(read more at Genetic Engineering News…)
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from Genetic Engineering News by Richard A. Stein
The contribution of individual cells to aggregate phenotypes is of increasing interest in biology, as is evident in the rise of technologies that can resolve cell-level details from the blur of population-level generalities. Among these technologies is RNA sequencing (RNA-seq), which can take snapshots of the transcriptome, capturing fleeting expression profiles, zooming in on single cells, and exposing cell-cell variations.
At present, RNA-seq is helping researchers take a fresh look at biological phenomena such as development, malignant transformation, and the behavior of microbial populations. Already, the new views are yielding conceptual advances.
One of the fundamental problems in dissecting the link between genotype and phenotype is that biological samples are usually complex mixtures of cells. In certain cases, such as with blood, there is a relatively good agreement as to the identity of the major cellular components. “In other cases, such as with tumors, there are unknown mixtures of different cell types and states that drive the ensemble behaviors we observe,” adds Dr. Shalek.
One of the promises of single-cell genomics is the possibility of performing transcriptome-wide analyses of the genes expressed by each cell. By uncovering patterns in gene expression and co-variation, researchers can identify what cell types are present and which pathways are active or silent.
(read more at Genetic Engineering News…)
Related Posts
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Atlas of the brain’s striatum could guide researchers to new drug treatments
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
Precursor tRNAs sense temperature changes: heat stress-induced capped pre-tRNAs suppress protein synthesis
Ketamine increases neuroplasticity in female mice but not in males
Somatic mutations linked to vascular damage in progeria
Scientists map dormant cancer cells’ hideouts, opening new targets for treatment
Soluble signals released by neighboring cells direct how the human kidney is built
Genetics influence how cancer arises – and how it evolves
RNA-based testing uncovers extraordinary diversity in mutations driving lung cancer
Study offers new insights into why ex-smokers remain at elevated risk of lung disease
Learning the grammar of gene regulation
New findings could transform new treatment for rare brain tumor astroblastoma
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